This repo covers most of the work done for creating the image processing tool "Fibar". The dev branch is for development, while the main branch is for users who would like to setup the tool or test the tool out.
The goal of this project is to provide an automated microscopy image analysis tool for complex biomaterials. These are samples of electrospun fibers with encapsulated components, such as bacteria, drugs etc. The tool is divided into two pipelines - one for fiber diameter measuring, the other for bacterial cell analysis. The ultimate goal of this tool is to reduce the workload of the researcher by providing a viable alternative to the manual analysis.
The main branch of the repo includes 3 main folders: Tool_setup, Data and Quick_runs.
The Tool_setup folder can be used when the user wants to setup the whole system. This system is being triggered by the Task Scheduler in Windows OS (a task example in .xml format is provided in the folder). The user can modifiy the parameters for triggerring the task themselves. It is suggested to create a separate Python virtual environment for the executable path. Additionally, some folder paths ought to be changed in the runner.py and the main.py files in the respective pipelines. The specific lines are marked with comments in the code.
The Data folder includes subfolder with microscopy data (SEM_images and CZI_files) for testing out both pipelines.
The Quick_runs folder is just a more direct way for the reader to test out some pipelines with the example data provided. In separate subfolders, the main.py can be run using the command line.
- In case of the Diameter measuring pipeline, 3 arguments should be provided by the user: absolute file path of the SEM image, name of method ("U-Net" or "Classical"), number of diameter measurements (for example,
python3 Quick_runs/Diameter_measuring_pipeline/main.py Data/SEM_images/10k_example.tif "U-Net" 10). The output of this pipeline is a list of diameter values as well as visualization of the diameters on the original image. (The visualization is an approximation and some obscure lines may occur which do not reflect the actual diameter values) - In case of the bacterial cell pipeline, 1 arguments should be provided by the user: absolute file path of the CZI file (for example,
python3 Quick_runs/Bacterial_cell_pipeline/main.py Data/CZI_files/ex_1.czi). Runnning this pipeline will output the amount of red and green bacteria found in the sample.
The user should be reminded about the constraints of the pipelines, which are provided in the thesis as well as below.
The pipelines should be executed in the Python 3.8.10 environment (have not tested out other versions yet). All of the required libraries and their versions can
be installed from the requirements.txt file.
NB! for scale obtaining to work properly with Pytesseract, please make sure the Tesseract-OCR has been installed to your system and the tesseract.exe path has been added to scale_obtain.py in the commented location. A Stack Overflow post about the setup is provided here. When receiving an error regarding eng.traineddata, do follow this post here.
For the fiber analysis pipeline, the system assumes the following:
- the SEM input image can be TIF/PNG/JPG format;
- the file name should include "2k" or "5k" if a magnification of 2k (2000x) or 5k (5000x) was used;
- the OCR part of the pipeline assumes that the value and unit are provided in white highlighted in black and the horizontal bar is white on a transparent background aligned below the value and unit;
- the scale can have values 1, 2, 3, 10, 200 or 400 and units, nm or um.
In case of the bacterial analysis pipeline, the following is expected:
- the input file is CZI format;
- the user has used red and green detectors to collect the data from the sample;
- staining dyes or fluorescent proteins have been used in the experiment (that have resulted in filled fluorescent bacteria);
- the shape of the raw data has the shape (I,T,C,Y,X) where I (illumination) and T (time) have values of 0;
- the input file can have up to 4 channels, but it needs to includes at least 2 channels for the red and green color.
Create an "Issue" under "Issues" and let's try to fix it.